Global prevalence of excessive daytime sleepiness among nurses: A systematic review and meta‐analysis

Abstract

BackgroundNurses face significant risks of excessive daytime sleepiness (EDS), which adversely affects workplace safety and productivity. Yet, the extent of EDS in this workforce remains inadequately characterized.AimThe aims of this systematic review were to assess the pooled prevalence of EDS among nurses.MethodologyWe systematically searched PubMed, Embase, Scopus, and ISI Web of Science for observational studies reporting the prevalence of EDS, as measured by the Epworth Sleepiness Scale (ESS), from database inception to May 1, 2024, with no language restrictions. Study quality was evaluated using JBI's critical appraisal tool. Pooled estimates were calculated through random‐effects meta‐analysis, with subgroup and meta‐regression analyses assessing associations between EDS prevalence and study‐level factors. Linear regression modeling was used to assess time trends. This study was registered with PROSPERO (CRD42024535109).ResultsWe included 36 unique studies encompassing 2677 nurses from 20 countries. EDS occurred in 14.0%–55.6% of nurses. The results of the meta‐analysis showed a pooled prevalence of EDS of 32.2% (95% confidence interval [CI]: 28.5–36.1; I2 = 92.6). Prevalence estimate did not vary substantially in terms of study‐level data (i.e., region, country income, pre/post covid era, hospital type, proportion of female nurse, average nursing experience, or proportion of married nurses). The prevalence of EDS in nurses has remained unchanged over time.ConclusionsThis meta‐analysis identifies a high global prevalence of EDS among nurses, affecting nearly one‐third of this workforce. The findings underscore the urgent need for targeted interventions to mitigate EDS across diverse geographic and economic contexts.Implication for nursing and nursing policyThis study highlights the pervasive issue of EDS among nurses worldwide, necessitating comprehensive strategies to address this challenge across all regions, income levels, hospital settings, and demographic groups.